In this study, multivariate statistical techniques, such as discriminant, factor /principal component and cluster analyses were applied to water quality data set monitored in pre- and post- monsoon for twenty five locations during three years to investigate seasonal and spatial variations in river water quality. The variables were mainly divided into two categories viz., non-conservative – DO, BOD, COD, nitrates and phosphates and conservative parameters – TDS, conductivity, alkalinity, hardness, calcium, magnesium, sodium, potassium and sulfates. Trivial elevated values of all non conservative Characteristics in pre-monsoon and some conservative parameters (SO4, Cl) in post-monsoon period reflected contribution on temporal effect on surface water. Results of principal component analysis evinced that all the parameters equally and significantly contribute to water quality variations in the river basin for both the seasons. Factor 1 and factor 2 analysis revealed the inverse relation of DO, indicating the control of dissolved oxygen on organic load and nutrients in different seasons. Hierarchical cluster analysis grouped twenty five stations into three clusters in pre-monsoon and six clusters in post- monsoon with similar water quality features. Third clustered group of former and sixth of latter consisted one station (St.25), exhibiting significant spatial variation in physico-chemical composition.
Key words: Multivariate analysis, cauvery, cluster, conservative parameters, temporal and spatial variations.
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